1580158
/
automatic
mirror of https://github.com/vladmandic/automatic
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Revert "update settings" 

This reverts commit e442172423.
pull/2138/head
Aptronymist 2023-09-06 11:07:51 -04:00
parent e442172423
commit e3268bf6c4
2 changed files with 17 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
.vscode/settings.json vendored
View File

@ -10,6 +10,5 @@
"./repositories/stable-diffusion-stability-ai",
"./repositories/stable-diffusion-stability-ai/ldm"
],
"python.analysis.typeCheckingMode": "off",
"editor.tabCompletion": "on"
"python.analysis.typeCheckingMode": "off"
}

33
modules/shared.py
View File

@ -350,7 +350,7 @@ else: # cuda
options_templates.update(options_section(('sd', "Execution & Models"), {
"sd_backend": OptionInfo("diffusers" if cmd_opts.use_openvino else "original", "Execution backend", gr.Radio, lambda: {"choices": ["original", "diffusers"] }),
"sd_checkpoint_autoload": OptionInfo(True, "Autoload Checkpoint on server startup"),
"sd_checkpoint_autoload": OptionInfo(True, "Model autoload on server start"),
"sd_model_checkpoint": OptionInfo(default_checkpoint, "Base model", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
"sd_model_refiner": OptionInfo('None', "Refiner model", gr.Dropdown, lambda: {"choices": ['None'] + list_checkpoint_tiles()}, refresh=refresh_checkpoints),
"sd_checkpoint_cache": OptionInfo(0, "Number of cached models", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
@ -366,24 +366,22 @@ options_templates.update(options_section(('sd', "Execution & Models"), {
}))
options_templates.update(options_section(('optimizations', "Optimizations"), {
"optimization_sep_note": OptionInfo("<h4>Reload Model to Apply Most Options Below</h4>", "", gr.HTML),
"cross_attention_optimization": OptionInfo(cross_attention_optimization_default, "Cross-attention optimization method (Reload Model Required)", gr.Radio, lambda: {"choices": shared_items.list_crossattention() }),
"cross_attention_optimization": OptionInfo(cross_attention_optimization_default, "Cross-attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention() }),
"cross_attention_options": OptionInfo([], "Cross-attention advanced options", gr.CheckboxGroup, lambda: {"choices": ['xFormers enable flash Attention', 'SDP disable memory attention']}),
"sub_quad_q_chunk_size": OptionInfo(512, "Sub-quadratic cross-attention query chunk size", gr.Slider, {"minimum": 16, "maximum": 8192, "step": 8}),
"sub_quad_kv_chunk_size": OptionInfo(512, "Sub-quadratic cross-attention kv chunk size", gr.Slider, {"minimum": 0, "maximum": 8192, "step": 8}),
"sub_quad_chunk_threshold": OptionInfo(80, "Sub-quadratic cross-attention chunking threshold", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1}),
"token_merging_ratio": OptionInfo(0.0, "Token merging ratio (Performance/Quality Tradeoff)", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}),
"token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img (Performance/Quality Tradeoff)", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}),
"token_merging_ratio_hr": OptionInfo(0.0, "Token merging ratio for hires pass (Performance/Quality Tradeoff)", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}),
's_min_uncond': OptionInfo(0.0, "Negative Guidance Cutoff (original backend)", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "step": 0.01}),
"sd_vae_sliced_encode": OptionInfo(False, "Sliced VAE Encoding for Second Pass batching (original backend)"),
"token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}),
"token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}),
"token_merging_ratio_hr": OptionInfo(0.0, "Token merging ratio for hires pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}),
"sd_vae_sliced_encode": OptionInfo(False, "VAE Slicing (original)"),
}))
options_templates.update(options_section(('cuda', "Compute Settings"), {
"compute_sep_note": OptionInfo("<h4>Reload Model to Apply Most Options Below</h4>", "", gr.HTML),
"memmon_poll_rate": OptionInfo(2, "VRAM usage polls per second during generation", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
"precision": OptionInfo("Autocast", "Precision type", gr.Radio, lambda: {"choices": ["Autocast", "Full"]}),
"cuda_dtype": OptionInfo("FP32" if sys.platform == "darwin" or cmd_opts.use_openvino else "BF16" if devices.backend == "ipex" else "FP16", "Device precision type", gr.Radio, lambda: {"choices": ["FP32", "FP16", "BF16"]}),
"no_half": OptionInfo(False, "Use full precision for model (--no-half) ", None, None, None),
"no_half": OptionInfo(False, "Use full precision for model (--no-half)", None, None, None),
"no_half_vae": OptionInfo(False, "Use full precision for VAE (--no-half-vae)"),
"upcast_sampling": OptionInfo(True if sys.platform == "darwin" else False, "Enable upcast sampling"),
"upcast_attn": OptionInfo(False, "Enable upcast cross attention layer"),
@ -391,10 +389,10 @@ options_templates.update(options_section(('cuda', "Compute Settings"), {
"disable_nan_check": OptionInfo(True, "Disable NaN check in produced images/latent spaces", gr.Checkbox, {"visible": False}),
"rollback_vae": OptionInfo(False, "Attempt VAE roll back when produced NaN values (experimental)"),
"opt_channelslast": OptionInfo(False, "Use channels last as torch memory format "),
"cudnn_benchmark": OptionInfo(False, "Enable full-depth cuDNN benchmark feature (nVidia)"),
"cudnn_benchmark": OptionInfo(False, "Enable full-depth cuDNN benchmark feature"),
# "cuda_allow_tf32": OptionInfo(True, "Allow TF32 math ops"),
# "cuda_allow_tf16_reduced": OptionInfo(True, "Allow TF16 reduced precision math ops"),
"cuda_compile": OptionInfo(True if cmd_opts.use_openvino else False, "Enable model compile (Linux only)"),
"cuda_compile": OptionInfo(True if cmd_opts.use_openvino else False, "Enable model compile"),
"cuda_compile_backend": OptionInfo("openvino_fx" if cmd_opts.use_openvino else "none", "Model compile backend", gr.Radio, lambda: {"choices": ['none', 'inductor', 'cudagraphs', 'aot_ts_nvfuser', 'hidet', 'ipex', 'openvino_fx']}),
"cuda_compile_mode": OptionInfo("default", "Model compile mode", gr.Radio, lambda: {"choices": ['default', 'reduce-overhead', 'max-autotune']}),
"cuda_compile_fullgraph": OptionInfo(False, "Model compile fullgraph"),
@ -412,12 +410,12 @@ options_templates.update(options_section(('diffusers', "Diffusers Settings"), {
"diffusers_move_refiner": OptionInfo(True, "Move refiner model to CPU when not in use"),
"diffusers_extract_ema": OptionInfo(True, "Use model EMA weights when possible"),
"diffusers_generator_device": OptionInfo("default", "Generator device", gr.Radio, lambda: {"choices": ["default", "cpu"]}),
"diffusers_model_cpu_offload": OptionInfo(False, "Model CPU offload (--medvram) (Overrides Move options)"),
"diffusers_seq_cpu_offload": OptionInfo(False, "Sequential CPU offload (--lowvram) (Overrides Model CPU and Move options)"),
"diffusers_model_cpu_offload": OptionInfo(False, "Enable model CPU offload (--medvram)"),
"diffusers_seq_cpu_offload": OptionInfo(False, "Enable sequential CPU offload (--lowvram)"),
"diffusers_vae_upcast": OptionInfo("default", "VAE upcasting", gr.Radio, lambda: {"choices": ['default', 'true', 'false']}),
"diffusers_vae_slicing": OptionInfo(True, "VAE Slicing"),
"diffusers_vae_tiling": OptionInfo(True, "VAE Tiling"),
"diffusers_attention_slicing": OptionInfo(False, "Attention Slicing (Not Recommended, but may improve performance)"),
"diffusers_vae_slicing": OptionInfo(True, "Enable VAE slicing"),
"diffusers_vae_tiling": OptionInfo(False if cmd_opts.use_openvino else True, "Enable VAE tiling"),
"diffusers_attention_slicing": OptionInfo(False, "Enable attention slicing"),
"diffusers_model_load_variant": OptionInfo("default", "Diffusers model loading variant", gr.Radio, lambda: {"choices": ['default', 'fp32', 'fp16']}),
"diffusers_vae_load_variant": OptionInfo("default", "Diffusers VAE loading variant", gr.Radio, lambda: {"choices": ['default', 'fp32', 'fp16']}),
"diffusers_lora_loader": OptionInfo("diffusers default" if cmd_opts.use_openvino else "sequential apply", "Diffusers LoRA loading variant", gr.Radio, lambda: {"choices": ['sequential apply', 'merge and apply', 'diffusers default']}),
@ -563,6 +561,7 @@ options_templates.update(options_section(('sampler-params', "Sampler Settings"),
"enable_quantization": OptionInfo(True, "Enable samplers quantization for sharper and cleaner results"),
"eta_ancestral": OptionInfo(1.0, "Noise multiplier for ancestral samplers (eta)", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_min_uncond': OptionInfo(0.0, "sigma negative guidance minimum ", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "step": 0.01}),
's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"),